Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation

This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined. The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies

Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding

In this work, we propose a subspace-based algorithm for DOA estimation which iteratively reduces the disturbance factors of the estimated data covariance matrix and incorporates prior knowledge which is gradually obtained on line. An analysis of the MSE of the reshaped data covariance matrix is carried out along with comparisons between computational complexities of the proposed and existing algorithms. Simulations focusing on closely-spaced sources, where they are uncorrelated and correlated, illustrate the improvements achieved.Comment: 7 figures. arXiv admin note: text overlap with arXiv:1703.1052

Bacterial Foraging Based Channel Equalizers

A channel equalizer is one of the most important subsystems in any digital communication receiver. It is also the subsystem that consumes maximum computation time in the receiver. Traditionally maximum-likelihood sequence estimation (MLSE) was the most popular form of equalizer. Owing to non-stationary characteristics of the communication channel MLSE receivers perform poorly. Under these circumstances ‘Maximum A-posteriori Probability (MAP)’ receivers also called Bayesian receivers perform better. Natural selection tends to eliminate animals with poor “foraging strategies” and favor the propagation of genes of those animals that have successful foraging strategies since they are more likely to enjoy reproductive success. After many generations, poor foraging strategies are either eliminated or shaped into good ones (redesigned). Logically, such evolutionary principles have led scientists in the field of “foraging theory” to hypothesize that it is appropriate to model the activity of foraging as an optimization process. This thesis presents an investigation on design of bacterial foraging based channel equalizer for digital communication. Extensive simulation studies shows that the performance of the proposed receiver is close to optimal receiver for variety of channel conditions. The proposed receiver also provides near optimal performance when channel suffers from nonlinearities

All-adaptive blind matched filtering for the equalization and identification of multipath channels: a practical approach

Blind matched filter receiver is advantageous over the state-of-the-art blind schemes due the simplicity in its implementation. To estimate the multipath communication channels, it uses neither any matrix decomposition methods nor statistics of the received data higher than the second order ones. On the other hand, the realization of the conventional blind matched filter receiver requires the noise variance to be estimated and the equalizer parameters to be calculated in state-space with relatively costly matrix operations. In this paper, a novel architecture is proposed to simplify a potential hardware implementation of the blind matched filter receiver. Our novel approach transforms the blind matched filter receiver into an all-adaptive format which replaces all the matrix operations. Furthermore, the novel design does not need for any extra step to estimate the noise variance. In this paper we also report on a comparative channel equalization and channel identification scenario, looking into the performances of the conventional and our novel all-adaptive blind matched filter receiver through simulations

Adaptive bootstrap signal separators for BPSK/QAM-modulated wireless CDMA systems in a multipath environment

CDMA is an attractive multiple-access scheme, because of its potential capacity increase and its anti-multipath fading capability. For satisfactory performance, however, the effect of the near-far problem has to be resolved. This problem can be combated by using power-control, which, however, results in an overall reduction in communication ranges, and thus in a loss of capacity. Among other methods for mitigating the near-far problem is the use of decorrelating receivers, both of fixed type, which directly utilizes the cross-correlation of the users codes, and of adaptive type, which uses recursive algorithms that leads to signal decorrelation. Not to lessen the importance of other adaptive algorithms, the current research concentrates on what was termed in the literature bootstrap algorithm . Although the emphasis will be on applying the adaptive bootstrap decorrelator, the fixed type will be used primarily to provide comparison. Also used for comparison are both blind adaptive and training sequence based MMSE. Most of the literature on multiuser detection has been assuming BPSK. However, a need for transferring wideband data demands using modulation schemes with high bits/cycle, such as QAM. Therefore, modification of the receiver is considered, so that QAM-modulation can be applied efficiently, using the complex signal approach of this modulation. For the asynchronous channel, vast amounts of research have been devoted to using one-shot matched filter banks followed by conventional decorrelators which implement the inverse of some (partial) correlation matrix. In this work, an adaptive bootstrap version is presented, which is suitable for the one-shot structure shown previously to be more robust to errors in delay estimation. It has also been noted that such a correlation matrix can, depending on the channel characteristics, become ill-conditioned or even singular. Therefore, another matched filtering structure, followed by what is called a multishot conventional (fixed type) decorrelator, has been previously suggested to mitigate this singularity problem. However, the fixed type of the multishot decorrelator is expected to have similar non-robustness to errors in delay estimation as was previously shown for the one-shot. Therefore, the adaptive multishot bootstrap decorrelator is presented and evaluated. Also, by adding an adaptive canceler, an extension to the above matched filter-decorrelator combination, will be proposed and evaluated. A multipath time-variant fading environment will be used in some of these performance evaluations. Finally, when handling multipath channels, the question is raised whether path combining should be done before or after the signals are decorrelated. For the asynchronous case, a one-shot extension of the bootstrap algorithm is presented, which is capable of decorrelating the signals from resolved paths of different users, to facilitate the decorrelate before combining case